Vehicle and method of controlling the same

ABSTRACT

A vehicle includes a camera unit disposed in the vehicle to have a plurality of channels and configured to obtain an image around the vehicle, the camera unit including one or more cameras, a sensing device including an ultrasonic sensor, the sensing device configured to obtain distance information between an object and the vehicle, and a controller configured to match a part of the image around the vehicle with at least one mask, form map information based on the at least one mask and the distance information, determine at least one control point based on the map information, and obtain the image around the vehicle based on a priority of the camera unit corresponding to a surrounding type of the vehicle determined based on the control point.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of Korean Patent Application No.10-2019-0166111, filed on Dec. 12, 2019 in the Korean IntellectualProperty Office, which application is hereby incorporated herein byreference.

TECHNICAL FIELD

The disclosure relates to a vehicle for recognizing an image around thevehicle, and a method of controlling the vehicle.

BACKGROUND

An autonomous driving technology of a vehicle is a technology in whichthe vehicle grasps a road condition and automatically drives even if adriver does not control a brake, a steering wheel, or an acceleratorpedal.

The autonomous driving technology is a core technology for smart carimplementation. For autonomous driving, the autonomous drivingtechnology may include highway driving assist (HDA, a technology thatautomatically maintains a distance between vehicles), blind spotdetection (BSD, a technology that detects surrounding vehicles duringreversing and sounds an alarm), autonomous emergency braking (AEB, atechnology that activates a braking system when the vehicle does notrecognize a preceding vehicle), lane departure warning system (LDWS),lane keeping assist system (LKAS, a technology that compensates fordeparting the lane without turn signals), advanced smart cruise control(ASCC, a technology that maintains a constant distance between vehiclesat a set speed and drives at a constant speed), traffic jam assistant(TJA), parking collision-avoidance assist (PCA), and remote smartparking assist (RSPA).

In particular, the RSPA system uses only an ultrasonic sensor for aparking space recognition, so it is possible to perform automaticparking by generating a control trajectory only when the vehicle isnearby.

In order to increase the completeness of the parking space without thevehicle or a parking arrangement, there is a need for a recognitionsystem that recognizes lane types outside the vehicle and transmits thelane types to a control system.

SUMMARY

An aspect of embodiments of the disclosure provides a vehicle capable ofefficient autonomous parking by changing a recognition area of a cameraaccording to a type of parking, and a method of controlling the vehicle.

Additional embodiments of the disclosure will be set forth in part inthe description which follows and, in part, will be obvious from thedescription, or may be learned by practice of the disclosure.

In accordance with an embodiment of the disclosure, a vehicle includes acamera disposed in a vehicle to have a plurality of channels andconfigured to obtain an image around the vehicle, a sensing deviceincluding an ultrasonic sensor and configured to obtain distanceinformation between an object and the vehicle, and a controllerconfigured to match a part of the image around the vehicle with at leastone mask, to form map information based on the at least one mask and thedistance information, to determine at least one control point based onthe map information, and to obtain the image around the vehicle based ona priority of the camera corresponding to a surrounding type of thevehicle determined based on the control point.

The map information may include the distance information correspondingto pixels of the image around the vehicle.

The controller may be configured to convert the image around the vehicleto a vehicle coordinate system to match with the at least one mask.

The controller may be configured to determine the surrounding type ofthe vehicle through learning of the image around the vehicle.

When performing longitudinal parking on a side of the vehicle, thecontroller may be configured to assign the priority to the channel onthe side of the vehicle among the plurality of channels.

When performing reverse diagonal parking of the vehicle, the controllermay be configured to assign the priority to the channel in front of thevehicle among the plurality of channels.

When performing forward diagonal parking of the vehicle, the controllermay be configured to assign the priority to the channel on the side ofthe vehicle among the plurality of channels.

When performing rear parking of the vehicle, the controller may beconfigured to assign the priority to the channel behind the vehicleamong the plurality of channels.

The controller may be configured to change the priority in real time inresponse to driving of the vehicle.

The vehicle may further include a display. The controller may beconfigured to form a top view image based on the map information of thevehicle, to form a boundary line on the top view based on priorityinformation and output the boundary line to the display.

In accordance with another aspect of the disclosure, a method ofcontrolling a vehicle includes obtaining, by a camera having a pluralityof channels, an image around the vehicle, obtaining, by a sensingdevice, distance information between an object and the vehicle,matching, by a controller, a part of the image around the vehicle withat least one mask, forming, by the controller, map information based onthe at least one mask and the distance information, determining, by thecontroller, at least one control point based on the map information, andobtaining, by the controller, the image around the vehicle based on apriority of the camera corresponding to a surrounding type of thevehicle determined based on the control point.

The map information may include the distance information correspondingto pixels of the image around the vehicle.

The matching of the part of the image around the vehicle with the atleast one mask may include converting the image around the vehicle to avehicle coordinate system to match with the at least one mask.

The obtaining of the image around the vehicle may include determiningthe surrounding type of the vehicle through learning of the image aroundthe vehicle.

The obtaining of the image around the vehicle may include giving thepriority to the channel on the side of the vehicle among the pluralityof channels when performing longitudinal parking on a side of thevehicle.

The obtaining of the image around the vehicle may include giving thepriority to the channel in front of the vehicle among the plurality ofchannels when performing reverse diagonal parking of the vehicle.

The obtaining of the image around the vehicle may include giving thepriority to the channel on the side of the vehicle among the pluralityof channels when performing forward diagonal parking of the vehicle.

The obtaining of the image around the vehicle may include giving thepriority to the channel behind the vehicle among the plurality ofchannels when performing rear parking of the vehicle.

The method may further include changing, by the controller, the priorityin real time in response to driving of the vehicle.

The method may further include forming, by the controller, a top viewimage based on the map information of the vehicle, and forming, by thecontroller, a boundary line on the top view based on priorityinformation and outputting the boundary line to the display.

BRIEF DESCRIPTION OF THE DRAWINGS

These and/or other aspects of the disclosure will become apparent andmore readily appreciated from the following description of theembodiments, taken in conjunction with the accompanying drawings, inwhich:

FIG. 1 is a control block diagram according to an embodiment;

FIG. 2 is a view for describing an operation of determining mapinformation based on an image around a vehicle according to anembodiment;

FIG. 3 is a view illustrating map information according to anembodiment;

FIG. 4 is a view illustrating that a control point is formed accordingto an embodiment;

FIGS. 5 to 8 are views for describing a priority of cameras assignedaccording to a surrounding type;

FIG. 9 is a view illustrating that a boundary is formed in a top viewimage according to an embodiment; and

FIG. 10 is a flowchart according to an embodiment.

DETAILED DESCRIPTION OF ILLUSTRATIVE EMBODIMENTS

Like reference numerals refer to like elements throughout thespecification. Not all elements of the embodiments of the disclosurewill be described, and the description of what are commonly known in theart or what overlap each other in the embodiments will be omitted. Theterms as used throughout the specification, such as “˜ part,” “˜module,” “˜ member,” “˜ block,” etc., may be implemented in softwareand/or hardware, and a plurality of “˜ parts,” “˜ modules,” “˜ members,”or “˜ blocks” may be implemented in a single element, or a single “˜part,” “˜ module,” “˜ member,” or “˜ block” may include a plurality ofelements.

It will be further understood that the term “connect” and itsderivatives refer both to direct and indirect connection, and theindirect connection includes a connection over a wireless communicationnetwork. The terms “include (or including)” and “comprise (orcomprising)” are inclusive or open-ended and do not exclude additional,unrecited elements or method steps, unless otherwise mentioned. It willbe further understood that the term “member” and its derivatives referboth to when a member is in contact with another member and when anothermember exists between the two members. It will be understood that,although the terms first, second, third, etc., may be used herein todescribe various elements, components, regions, layers and/or sections,these elements, components, regions, layers and/or sections should notbe limited by these terms. These terms are only used to distinguish oneelement, component, region, layer or section from another region, layeror section.

It is to be understood that the singular forms “a,” “an,” and “the”include plural references unless the context clearly dictates otherwise.Reference numerals used for method steps are merely used for convenienceof explanation, but not to limit an order of the steps. Thus, unless thecontext clearly dictates otherwise, the written order may be practicedotherwise.

Hereinafter, an operation principle and embodiments of the disclosurewill be described with reference to accompanying drawings.

FIG. 1 is a control block diagram according to an embodiment.

Referring to FIG. 1, a vehicle 1 according to an embodiment may includea camera unit 300, a sensing device 100, a display 400, and a controller200.

The camera unit 300 can include one or more cameras 300. The camera unit300 has a plurality of channels and may obtain images around the vehicle1. Hereinafter, the term “camera 300” may refer to the camera unit or anindividual camera or cameras of the camera unit.

The camera(s) 300 installed in the vehicle 1 may include acharge-coupled device (CCD) camera or a CMOS color image sensor. Here,both the CCD and the CMOS refer to a sensor that converts light receivedthrough the lens of the camera 300 into an electric signal and storesthe electric signal.

The sensing device 100 may include an ultrasonic sensor.

The ultrasonic sensor may employ a method of transmitting ultrasonicwaves and detecting a distance to an obstacle using ultrasonic wavesreflected on the obstacle.

The sensing device 100 may obtain distance information of the vehicle 1and the obstacle provided around the vehicle 1.

The display 400 may be provided as an instrument panel provided in thevehicle 1 or a display device provided in a center fascia.

The display 400 may include cathode ray tubes (CRTs), a digital lightprocessing (DLP) panel, a plasma display panel (PDP), a liquid crystaldisplay (LCD) panel, an electro luminescence (EL) panel, anelectrophoretic display (EPD) panel, an electrochromic display (ECD)panel, a light emitting diode (LED) panel or an organic light emittingdiode (OLED) panel, but is not limited thereto.

The controller 200 may match a part of an image around the vehicle 1with at least one mask. That is, the obstacle, a floor, or the likedisplayed in the image may be matched to a corresponding mask.

The controller 200 may form map information based on the at least onemask and the distance information.

The map information may refer to information including the distanceinformation between the vehicle 1 and the surrounding obstacle.

The controller 200 may obtain the image around the vehicle 1 based onthe priority of the camera 300 corresponding to the surrounding type ofthe vehicle 1 determined based on the map information.

The surrounding type may refer to a relationship between the vehicle 1and the obstacle, and a relationship between the vehicle 1 and a road.

The priority may refer to information related to a recognition area ofthe camera 300.

The map information may include the distance information correspondingto pixels of the image around the vehicle 1. That is, the mapinformation may be provided as information matching the distance betweenthe vehicle 1 and the obstacle and the pixels of the image around thevehicle 1.

The controller 200 may convert the image around the vehicle 1 into avehicle coordinate system to correspond to the at least one mask.

That is, the controller 200 may obtain the image around the vehicle 1with a coordinate system centered on the camera 300, but the controller200 may convert the image around the vehicle 1 into the coordinatesystem of the vehicle itself to form the map information.

The controller 200 may determine the surrounding type of the vehicle 1through learning of the image around the vehicle 1.

The learning performed by the controller 200 may be performed throughdeep learning.

The deep learning is a field of machine learning, and may refer to aform of expressing data as a vector or a graph, which can be processedby a computer and building a model for learning data.

The model of deep learning may be formed based on a neural network, andin particular, the model of deep learning may be formed by building upthe model by stacking multiple layers of neural networks.

When performing longitudinal parking on a side of the vehicle 1, thecontroller 200 may assign the priority to the channel on the side of thevehicle 1 among the plurality of channels.

When performing reverse diagonal parking of the vehicle 1, thecontroller 200 may assign the priority to the channel in front of thevehicle 1 among the plurality of channels.

When performing forward diagonal parking of the vehicle 1, thecontroller 200 may assign the priority to the channel on the side of thevehicle 1 among the plurality of channels.

When performing rear parking of the vehicle 1, the controller 200 mayassign the priority to the channel behind the vehicle 1 among theplurality of channels.

The controller 200 may change the priority in real time in response todriving of the vehicle 1.

The priority of the camera 300 changed in response to parking of theabove-described vehicle 1 will be described in detail below.

The controller 200 may form a top view image based on the mapinformation of the vehicle 1, and may form a boundary line in the topview based on priority information to output it to the display 400.

The boundary formed in the top view may refer to the recognition area ofeach of the cameras 300.

The controller 200 may be implemented with a memory storing an algorithmto control operation of the components in the vehicle 1 or data about aprogram that implements the algorithm, and a processor carrying out theaforementioned operation using the data stored in the memory. The memoryand the processor may be implemented in separate chips. Alternatively,the memory and the processor may be implemented in a single chip.

At least one component may be added or deleted corresponding to theperformance of the components of the vehicle 1 illustrated in FIG. 1. Itwill be readily understood by those skilled in the art that the mutualposition of the components may be changed corresponding to theperformance or structure of the vehicle 1.

In the meantime, each of the components illustrated in FIG. 1 may bereferred to as a hardware component such as software and/or a fieldprogrammable gate array (FPGA) and an application specific integratedcircuit (ASIC).

FIG. 2 is a view for describing an operation of determining mapinformation based on an image around a vehicle according to anembodiment, and FIG. 3 is a view illustrating map information accordingto an embodiment.

Referring to FIG. 2, it illustrates an external image V2 obtained by thevehicle 1. The cameras 300 provided in the vehicle 1 may be provided atthe front, rear, and side surfaces to obtain the image around thevehicle 1.

The controller 200 may match the mask with the obtained image around thevehicle 1.

Meanwhile, in this process, the controller 200 may convert thecoordinates of each of the cameras 300 to the coordinates of the vehicle1. Particularly, a mask M2-1 may be matched to the obstacle such as avehicle illustrated in the image around the vehicle 1.

In addition, an empty space on the road may be matched with a differentmask M2-2.

On the other hand, the floor or ground may be matched with another maskM2-3. The controller 200 may match the mask with the distanceinformation corresponding to each of the pixels.

The controller 200 may determine map information F2 based on thisoperation.

Meanwhile, in FIG. 2, the map information is derived based on a vehicleimage obtained by the camera 300 in response to one camera 300, but eachof the cameras 300 provided in the vehicle 1 may perform a correspondingoperation.

Meanwhile, when the map information of each of the cameras 300determined as described above is collected, map information F3illustrated in FIG. 3 may be finally derived.

The map information may be determined based on a recognition result ofthe camera 300 and the ultrasonic sensor and a distance coordinatesystem. The controller 200 may provide a method for providing a freespace and a control point for parking control using distance map datafor each of the pixels of each of the cameras 300 based on the mapinformation.

The above-described operation may form the map information based on theimage of the camera 300 suitable for spatial recognition according to atype of the parking space around the vehicle 1.

The operation minimizes an occlusion of the image and may quicklydetermine whether to recognize an occupied space.

In addition, the above-described map information may generate an optimaldistance map form for recognition by comparing the recognition resultsof the cameras 300 of different locations.

In addition, it is possible to optimize a control performance bygenerating the coordinates of an entry point necessary for a subjectcontrol.

Meanwhile, the distance map illustrated in FIG. 3 is only an example ofthe disclosure, and the distance map may be expressed in various forms,and there is no limitation in form.

FIG. 4 is a view illustrating that a control point is formed accordingto an embodiment.

Referring to FIG. 4, as described above, in a case of the mapinformation, the distance information may be included. The controller200 may control the vehicle 1 by forming control points P41, P42, andP43 of each obstacle instead of the entire obstacle to avoid eachcontrol point. That is, in the subject control of the controller 200, itis possible to maximize control efficiency using point information closeto a progress of the vehicle 1, rather than using the information ofeach obstacle. Hereinafter, the surrounding types that are subdividedbased on this will be described.

FIGS. 5 to 8 are views for describing a priority of cameras assignedaccording to a surrounding type.

Referring to FIG. 5, it represents the surrounding type in which aparking space S5 is formed on a right side of the vehicle 1.

Also, the controller 200 may control the vehicle 1 based on two controlpoints P51 and P52. Since the two control points are located on the sideof the vehicle, the controller 200 may assign a high priority to theside camera 300. The controller 200 may perform side parking by wideninga width of an area Ca51 recognized by the side camera 300.

Referring to FIG. 6, a case of the reverse diagonal parking isillustrated.

Even in this case, the controller 200 may control the vehicle 1 based ontwo control points P61 and P62. Although the two control points arelocated on the side of the vehicle 1, the two control points are locatedat positions of the control points different from those of FIG. 5, andtherefore, it is necessary to determine a front obstacle to park in thecorresponding parking area.

The controller 200 may assign a high priority to the front camera 300.The controller 200 may park in an area Ca6 i recognized by the frontcamera 300.

Referring to FIG. 7, a case of forward diagonal parking is illustrated.

Even in this case, the controller 200 may control the vehicle 1 based ontwo control points P71 and P72. Although the two control points arelocated on the side of the vehicle 1, the two control points are locatedat positions of the control points different from those of FIG. 6, andtherefore, it is necessary to determine a side obstacle to park in thecorresponding parking area.

The controller 200 may assign the high priority to the side camera 300.The controller 200 may park in an area Ca71 recognized by the sidecamera 300.

Referring to FIG. 8, it illustrates the surrounding type in which theparking space is at the rear of the vehicle 1.

The controller 200 may control the vehicle 1 based on two control pointsP81 and P82. Since the two control points are located at the rear of thevehicle, the controller 200 may assign the high priority to the rearcamera 300. The controller 200 may perform rear parking by widening thewidth of the area recognized by the rear camera 300.

On the other hand, in the driving of the vehicle 1, surroundingsituations may change in real time, and the position of the vehicle 1and the control point may also change in real time. Accordingly, thecontroller 200 may change the priority of the camera 300 by consideringa positional relationship between the vehicle 1 and the control point inreal time.

FIG. 9 is a view illustrating that a boundary is formed in a top viewimage according to an embodiment.

Referring to FIGS. 5 to 8, the recognition area of the camera 300provided in the vehicle 1 may be changed. Meanwhile, the controller 200may use information of the plurality of cameras 300 in forming the topview image, and may display the recognition area reflecting the priorityof the cameras 300 as the boundary on the top view image.

For example, in the case of FIG. 5 in which the vehicle 1 performslongitudinal side parking, a boundary line L81 having a largerecognition area of the side camera 300 may be displayed on the top viewimage.

On the other hand, when the vehicle 1 performs rear parking asillustrated in FIG. 8, a boundary line L82 having the large recognitionarea of the rear camera 300 may be displayed on the top view image.

Meanwhile, the above-described operations are only one embodiment fordescribing the operation of the disclosure, and there is no limitationin the operation of forming the map information according to thedistance and changing the priority or the recognition area of thecameras 300 accordingly.

FIG. 10 is a flowchart according to an embodiment.

Referring to FIG. 10, the vehicle 1 may obtain the image around thevehicle 1 and the distance information (1001).

In addition, the vehicle 1 may form the map information based on theimage around the vehicle 1 and the distance information (1002).

In addition, the map information may include the distance information ofeach obstacle, and the controller 200 may determine the control pointbased on the distance information of each obstacle (1003).

Also, the controller 200 may determine the surrounding type based on thepositional relationship between the vehicle 1 and the control point(1004).

In response to this type, the controller 200 may assign the priority toeach of the cameras 300 and control the vehicle 1 based on therecognition area of the camera 300 assigned the priority (1005).

According to the embodiments of the disclosure, the vehicle 1 and themethod of controlling the vehicle 1 may change the recognition area ofthe camera according to the type of parking, thereby enabling efficientautonomous parking.

The disclosed embodiments may be implemented in the form of a recordingmedium storing computer-executable instructions that are executable by aprocessor. The instructions may be stored in the form of a program code,and when executed by a processor, the instructions may generate aprogram module to perform operations of the disclosed embodiments. Therecording medium may be implemented as a non-transitorycomputer-readable recording medium.

The non-transitory computer-readable recording medium may include allkinds of recording media storing commands that can be interpreted by acomputer. For example, the non-transitory computer-readable recordingmedium may be, for example, ROM, RAM, a magnetic tape, a magnetic disc,flash memory, an optical data storage device, etc.

Embodiments of the disclosure have thus far been described withreference to the accompanying drawings. It should be obvious to a personof ordinary skill in the art that the disclosure may be practiced inother forms than the embodiments as described above without changing thetechnical idea or essential features of the disclosure. The aboveembodiments are only by way of example, and should not be interpreted ina limited sense.

What is claimed is:
 1. A vehicle comprising: a display; a camera unitdisposed in the vehicle, comprising a plurality of cameras; a sensingdevice including an ultrasonic sensor, the sensing device configured toobtain distance information between an object and the vehicle; and acontroller configured to: identify a free space based on images obtainedby the plurality of cameras, based on the free space, determine aparking direction in which the vehicle is to be parked, identify animage corresponding to the parking direction among the images obtainedby the plurality of cameras, generate a view image based on theidentified image and the remaining image among the images obtained bythe plurality of cameras, and control display of the view image,wherein, when the controlling the display of the view image, thecontroller is configured to: divide a display region of the display intoa plurality of regions based on a number of the plurality of cameras,and adjust a boundary of a region in which the identified image isdisplayed so that the region in which the identified image is displayedis displayed larger than each region in which the remaining images aredisplayed.
 2. The vehicle according to claim 1, wherein the controlleris configured to generate map information based on the distanceinformation between the object and the vehicle obtained by the sensingdevice, determine at least one control point based on the mapinformation, and control driving to avoid the at least one controlpoint, wherein the map information comprises the distance informationcorresponding to pixels of the images obtained by the plurality ofcameras.
 3. The vehicle according to claim 1, wherein the controller isconfigured to convert the images obtained by the plurality of cameras toa vehicle coordinate system to match with a mask.
 4. The vehicleaccording to claim 1, wherein the controller is configured to determinea surrounding type of the vehicle based on the identified free space,wherein the surrounding type further includes a relationship between theobject and the vehicle, and a relationship between a road and thevehicle, wherein the controller is configured to determine thesurrounding type of the vehicle through learning of the images obtainedby the plurality of cameras.
 5. The vehicle according to claim 4,wherein, when the surrounding type of the vehicle is longitudinalparking on a side of the vehicle, the controller is configured to assigna high priority to a camera on the side of the vehicle among theplurality of cameras.
 6. The vehicle according to claim 4, wherein, whenthe surrounding type of the vehicle is reverse diagonal parking of thevehicle, the controller is configured to assign a high priority to acamera in front of the vehicle among the plurality of cameras.
 7. Thevehicle according to claim 4, wherein, when the surrounding type of thevehicle is forward diagonal parking of the vehicle, the controller isconfigured to assign a high priority to a camera on a side of thevehicle among the plurality of cameras.
 8. The vehicle according toclaim 4, wherein, when the surrounding type of the vehicle is rearparking of the vehicle, the controller is configured to assign a highpriority to a camera behind the vehicle among the plurality of cameras.9. The vehicle according to claim 1, wherein the controller isconfigured to assign a priority for the plurality of cameras based onthe parking direction, and change the priority in real time in responseto driving of the vehicle.
 10. The vehicle according to claim 9, whereinthe controller is configured form a boundary line on the view imagebased on priority information of the plurality of cameras and output theboundary line to the display.
 11. A method of controlling a vehicle, themethod comprising: obtaining, by a camera unit having a plurality ofcameras, images around the vehicle; obtaining, by a sensing device,distance information between an object and the vehicle; identifying afree space based on images obtained by the plurality of cameras;determining a parking direction in which the vehicle is to be parked,based on the free space; identifying an image corresponding to theparking direction among the images obtained by the plurality of cameras;generating a view image based on the identified image and the remainingimage among the images obtained by the plurality of cameras; anddisplaying, by the display, the view image, wherein the controlling thedisplay of the view image includes: dividing a display region of thedisplay into a plurality of regions based on a number of the pluralityof cameras, and adjusting a boundary of a region in which the identifiedimage is displayed so that the region in which the identified image isdisplayed is displayed larger than each region in which the remainingimages are displayed.
 12. The method according to claim 11, furthercomprising: generating map information based on the distance informationbetween the object and the vehicle obtained by the sensing device,wherein the map information comprises the distance informationcorresponding to pixels of the images obtained by the plurality ofcameras.
 13. The method according to claim 11, further comprisingconverting the images obtained by the plurality of cameras to a vehiclecoordinate system to match with a mask.
 14. The method according toclaim 11, further comprising determining a surrounding type of thevehicle based on the identified free space, wherein the surrounding typefurther includes a relationship between the object and the vehicle, anda relationship between a road and the vehicle, wherein obtaining theimage around the vehicle comprises determining the surrounding type ofthe vehicle through learning of the images obtained by the plurality ofcameras.
 15. The method according to claim 14, wherein obtaining theimages obtained by the plurality of cameras comprises giving a highpriority to a camera on a side of the vehicle among the plurality ofcameras when the surrounding type of the vehicle is longitudinal parkingon the side of the vehicle.
 16. The method according to claim 14,wherein obtaining the image around the vehicle comprises giving a highpriority to a camera in front of the vehicle among the plurality ofcameras when the surrounding type of the vehicle is reverse diagonalparking of the vehicle.
 17. The method according to claim 14, whereinobtaining the image around the vehicle comprises giving a high priorityto a camera on a side of the vehicle among the plurality of cameras whenthe surrounding type of the vehicle is forward diagonal parking of thevehicle.
 18. The method according to claim 14, wherein obtaining theimage around the vehicle comprises giving a high priority to a camerabehind the vehicle among the plurality of cameras when the surroundingtype of the vehicle is rear parking of the vehicle.
 19. The methodaccording to claim 11, further comprising assign a priority for theplurality of cameras based on the parking direction, and changing thepriority in real time in response to driving of the vehicle.
 20. Themethod according to claim 19, further comprising: forming a boundaryline on the view image based on the priority of the plurality ofcameras; and outputting the boundary line to the display.